Missing data techniques using voicing probability dor robust automatic speech recognition

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dc.contributor.authorKim, LYko
dc.contributor.authorCho, HYko
dc.contributor.authorOh, Yung-Hwanko
dc.date.accessioned2010-03-22T08:51:51Z-
dc.date.available2010-03-22T08:51:51Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2001-05-
dc.identifier.citationELECTRONICS LETTERS, v.37, no.11, pp.723 - 724-
dc.identifier.issn0013-5194-
dc.identifier.urihttp://hdl.handle.net/10203/17274-
dc.description.abstractThe authors propose a new method for detecting missing data by utilising voicing probability under a missing data theory. With the same level of distortion, people fail to recognise vowels more frequently than consonants. From this observation, we Propose that consonants should not be classified into missing data. The experimental results showed that our method significantly improves the performance for isolated word recognition under various noise environments.-
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherINST ENGINEERING TECHNOLOGY-IET-
dc.titleMissing data techniques using voicing probability dor robust automatic speech recognition-
dc.typeArticle-
dc.identifier.wosid000169192000040-
dc.type.rimsART-
dc.citation.volume37-
dc.citation.issue11-
dc.citation.beginningpage723-
dc.citation.endingpage724-
dc.citation.publicationnameELECTRONICS LETTERS-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorOh, Yung-Hwan-
dc.contributor.nonIdAuthorKim, LY-
dc.contributor.nonIdAuthorCho, HY-
dc.type.journalArticleArticle-
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